Nevin Manimala

Clin Infect Dis. 2021 Jul 14:ciab630. doi: 10.1093/cid/ciab630. Online ahead of print.

ABSTRACT

Although interim results from several large placebo-controlled phase 3 trials demonstrated high vaccine efficacy (VE) against symptomatic COVID-19, it is unknown how effective the vaccines are in preventing people from becoming asymptomatically in- fected and potentially spreading the virus unwittingly. It is more difficult to evaluate VE against SARS-CoV-2 infection than against symptomatic COVID-19 because infection is not observed directly but rather is known to occur between two antibody or RT-PCR tests. Ad- ditional challenges arise as community transmission changes over time and as participants are vaccinated on different dates because of staggered enrollment of participants or crossover of placebo recipients to the vaccine arm before the end of the study. Here, we provide valid and efficient statistical methods for estimating potentially waning VE against SARS-CoV-2 infection with blood or nasal samples under time-varying community transmission, stag- gered enrollment, and blinded or unblinded crossover. We demonstrate the usefulness of the proposed methods through numerical studies mimicking the BNT162b2 phase 3 trial and the Prevent COVID U study. In addition, we assess how crossover and the frequency of diagnostic tests affect the precision of VE estimates.

PMID:34260716 | DOI:10.1093/cid/ciab630

Bioinformatics. 2021 Jul 14:btab514. doi: 10.1093/bioinformatics/btab514. Online ahead of print.

ABSTRACT

MOTIVATION: Identification and interpretation of noncoding variations that affect disease risk remain a paramount challenge in genome-wide association studies (GWAS) of complex diseases. Experimental efforts have provided comprehensive annotations of functional elements in the human genome. On the other hand, advances in computational biology, especially machine learning approaches, have facilitated accurate predictions of cell-type-specific functional annotations. Integrating functional annotations with GWAS signals has advanced the understanding of disease mechanisms. In previous studies, functional annotations were treated as static of a genomic region, ignoring potential functional differences imposed by different genotypes across individuals.

RESULTS: We develop a computational approach, Openness Weighted Association Studies (OWAS), to leverage and aggregate predictions of chromosome accessibility in personal genomes for prioritizing GWAS signals. The approach relies on an analytical expression we derived for identifying disease associated genomic segments whose effects in the etiology of complex diseases are evaluated. In extensive simulations and real data analysis, OWAS identifies genes/segments that explain more heritability than existing methods, and has a better replication rate in independent cohorts than GWAS. Moreover, the identified genes/segments show tissue-specific patterns and are enriched in disease relevant pathways. We use rheumatic arthritis (RA) and asthma (ATH) as examples to demonstrate how OWAS can be exploited to provide novel insights on complex diseases.

AVAILABILITY: The R package OWAS that implements our method is available at https://github.com/shuangsong0110/OWAS.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34260700 | DOI:10.1093/bioinformatics/btab514

Rheumatology (Oxford). 2021 Jul 14:keab544. doi: 10.1093/rheumatology/keab544. Online ahead of print.

ABSTRACT

OBJECTIVES: Age at onset is useful in identifying chronic back patients at an increased risk of axial spondyloarthritis (axSpA). Yet, the majority of data on which the age at onset <45 years criterion was based originates from Europe. Therefore, it is unknown if this criterion applies in other parts of the world. We aimed to assess age at onset of axSpA and its relationship with HLA-B27 and gender across the world.

METHODS: Analyses were applied to patients from 24 countries across the world with an axSpA diagnosis and known age at onset of axial complaints. Cumulative probability plots were used to display the cumulative distribution of age at onset of axial symptoms. Linear regression models were built to assess the effect of HLA-B27 and gender on age at onset of axial symptoms.

RESULTS: 92% of 2,579 axSpA patients had an age at onset of axial symptoms <45 years, with only small variations across the geographical regions (Asia [n = 574; 94%], Europe & North America [n = 988; 92%], Latin America [n = 246; 89%], and Middle East & North Africa [n = 771; 91%]). Age at onset of axial symptoms was consistently lower in HLA-B27 positive patients (median 25[19-32] vs 31[22-39]) and male patients (median 25[19-33] vs 28[21-37]), but in multivariable models an additional statistically significant effect of male gender independent of HLA-B27 was only found in Asia.

CONCLUSION: Around the world, the large majority of axSpA patients had an age at onset of axial disease <45, with HLA-B27 and male gender associated with earlier disease onset.

PMID:34260699 | DOI:10.1093/rheumatology/keab544

Brief Bioinform. 2021 Jul 15:bbab262. doi: 10.1093/bib/bbab262. Online ahead of print.

ABSTRACT

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the newly discovered coronavirus, SARS-CoV-2. Increased severity of COVID-19 has been observed in patients with diabetes mellitus (DM). This study aimed to identify common transcriptional signatures, regulators and pathways between COVID-19 and DM. We have integrated human whole-genome transcriptomic datasets from COVID-19 and DM, followed by functional assessment with gene ontology (GO) and pathway analyses. In peripheral blood mononuclear cells (PBMCs), among the upregulated differentially expressed genes (DEGs), 32 were found to be commonly modulated in COVID-19 and type 2 diabetes (T2D), while 10 DEGs were commonly downregulated. As regards type 1 diabetes (T1D), 21 DEGs were commonly upregulated, and 29 DEGs were commonly downregulated in COVID-19 and T1D. Moreover, 35 DEGs were commonly upregulated in SARS-CoV-2 infected pancreas organoids and T2D islets, while 14 were commonly downregulated. Several GO terms were found in common between COVID-19 and DM. Prediction of the putative transcription factors involved in the upregulation of genes in COVID-19 and DM identified RELA to be implicated in both PBMCs and pancreas. Here, for the first time, we have characterized the biological processes and pathways commonly dysregulated in COVID-19 and DM, which could be in the next future used for the design of personalized treatment of COVID-19 patients suffering from DM as comorbidity.

PMID:34260684 | DOI:10.1093/bib/bbab262

PLoS Pathog. 2021 Jul 14;17(7):e1009753. doi: 10.1371/journal.ppat.1009753. Online ahead of print.

ABSTRACT

To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results suggest that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings suggest biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.

PMID:34260666 | DOI:10.1371/journal.ppat.1009753

PLoS One. 2021 Jul 14;16(7):e0254458. doi: 10.1371/journal.pone.0254458. eCollection 2021.

ABSTRACT

The issues of personality and its relations with the level of empathetic sensibility of medical doctors are broadly discussed in the literature. The aim of this study was an assessment of personality related predictors of empathy indicators in female and male students of medicine with consideration of gender differences. Methods applied were Empathic Sensitiveness Scale (ESS) and Personality Inventory (NEO-PI-R). The study included 153 participants, who were students of the fifth year of medical studies. Students filled in questionnaires during workshops in clinical psychological skills. Participation in the study was voluntary and anonymous. The statistical analysis was performed using Statistica 13 PL and PS IMAGO PRO (SPSS). Linear regression analysis with the interaction component was performed to explore the relationship between personality factors and gender and their interaction with the variable dependent level of empathy. The analysis showed that Extraversion, Openness and Agreeableness are associated with the level of Empathic Concern. Neuroticism, Extraversion, Agreeableness and Conscientiousness are associated with the level of Personal Distress. Extraversion, Openness, Agreeableness and Conscientiousness are associated with the level of Perspective-taking. The regression analysis with the interactive component showed that there is no relationship between gender and the level of empathy, therefore the interactions were insignificant. Empathetic sensibility is related to personality dimensions of the students of medicine. Although there has been no interaction among chief personality dimensions, empathy indicators and gender, detailed analysis of personality dimensions’ components has shown differences between men and women.

PMID:34260654 | DOI:10.1371/journal.pone.0254458

PLoS One. 2021 Jul 14;16(7):e0254601. doi: 10.1371/journal.pone.0254601. eCollection 2021.

ABSTRACT

Previous research has identified a predictive model of how a nation’s distribution of gross domestic product (GDP) among agriculture (a), industry (i), and services (s) changes as a country develops. Here we use this national model to analyze the composition of GDP for US Metropolitan Statistical Areas (MSA) over time. To characterize the transfer of GDP shares between the sectors in the course of economic development we explore a simple system of differential equations proposed in the country-level model. Fitting the model to more than 120 MSAs we find that according to the obtained parameters MSAs can be classified into 6 groups (consecutive, high industry, re-industrializing; each of them also with reversed development direction). The consecutive transfer (a → i → s) is common but does not represent all MSAs examined. At the 95% confidence level, 40% of MSAs belong to types exhibiting an increasing share of GDP from agriculture. In California, such MSAs, which we classify as part of an agriculture renaissance, are found in the Central Valley.

PMID:34260653 | DOI:10.1371/journal.pone.0254601

PLoS One. 2021 Jul 14;16(7):e0253940. doi: 10.1371/journal.pone.0253940. eCollection 2021.

ABSTRACT

Empirical research on human mortality and extreme longevity suggests that the risk of death among the oldest-old ceases to increase and levels off at age 110. The universality of this finding remains in dispute because of two main reasons: i) high uncertainty around statistical estimates generated from scarce data, and ii) the lack of country-specific comparisons. In this article, we estimate age patterns of mortality above age 105 using data from the International Database on Longevity, an exceptionally large and recently updated database comprising more than 13,000 validated records of long-lived individuals from eight populations. We show that, in all of them, similar mortality trajectories arise, suggesting that the risk of dying levels off after age 105. As more high-quality data become available, there is more evidence in support of a levelling-off of the risk of dying as a regularity of longevous populations.

PMID:34260647 | DOI:10.1371/journal.pone.0253940

PLoS One. 2021 Jul 14;16(7):e0254639. doi: 10.1371/journal.pone.0254639. eCollection 2021.

ABSTRACT

OBJECTIVE: Late-life depression and subjective cognitive decline (SCD) are significant risk factors for dementia. However, studies with a large sample size are needed to clarify their independent and combined risks for subsequent dementia.

METHODS: This nationwide population-based cohort study included all individuals aged 66 years who participated in the National Screening Program between 2009 and 2013 (N = 939,099). Subjects were followed from the day they underwent screening to the diagnosis of dementia, death, or the last follow-up day (December 31, 2017).

RESULTS: Depressive symptom presentation, recent depressive disorder, and SCD independently increased dementia incidence with adjusted hazard ratio (aHR) of 1.286 (95% CI:1.255-1.318), 1.697 (95% CI:1.621-1.776), and 1.748 (95% CI: 689-1.808) respectively. Subjects having both SCD and depression had a higher risk (aHR = 2.466, 95% CI:2.383-2.551) of dementia than having depression (aHR = 1.402, 95% CI:1.364-1.441) or SCD (aHR = 1.748, 95% CI:1.689-1.808) alone.

CONCLUSIONS: Depressive symptoms, depressive disorder, and SCD are independent risk factors for dementia. Co-occurring depression and SCD have an additive effect on the risk of dementia; thus, early intervention and close follow up are necessary for patients with co-occurring SCD and depression.

PMID:34260630 | DOI:10.1371/journal.pone.0254639

PLoS One. 2021 Jul 14;16(7):e0253721. doi: 10.1371/journal.pone.0253721. eCollection 2021.

ABSTRACT

The sex ratio at birth (SRB, i.e., the ratio of male to female births) in Vietnam has been imbalanced since the 2000s. Previous studies have revealed a rapid increase in the SRB over the past 15 years and the presence of important variations across regions. More recent studies suggested that the nation’s SRB may have plateaued during the 2010s. Given the lack of exhaustive birth registration data in Vietnam, it is necessary to estimate and project levels and trends in the regional SRBs in Vietnam based on a reproducible statistical approach. We compiled an extensive database on regional Vietnam SRBs based on all publicly available surveys and censuses and used a Bayesian hierarchical time series mixture model to estimate and project SRB in Vietnam by region from 1980 to 2050. The Bayesian model incorporates the uncertainties from the observations and year-by-year natural fluctuation. It includes a binary parameter to detect the existence of sex ratio transitions among Vietnamese regions. Furthermore, we model the SRB imbalance using a trapezoid function to capture the increase, stagnation, and decrease of the sex ratio transition by Vietnamese regions. The model results show that four out of six Vietnamese regions, namely, Northern Midlands and Mountain Areas, Northern Central and Central Coastal Areas, Red River Delta, and South East, have existing sex imbalances at birth. The rise in SRB in the Red River Delta was the fastest, as it took only 12 years and was more pronounced, with the SRB reaching the local maximum of 1.146 with a 95% credible interval (1.129, 1.163) in 2013. The model projections suggest that the current decade will record a sustained decline in sex imbalances at birth, and the SRB should be back to the national SRB baseline level of 1.06 in all regions by the mid-2030s.

PMID:34260618 | DOI:10.1371/journal.pone.0253721